Graph-Based Flight Gate Assignment and Arrival Delay Prediction using Machine Learning and Graph Neural Networks

The main contributions of this research are:
1) Constructing a flight conflict graph based on overlapping flight operations.
2) Experimenting the performance of Greedy Coloring and DSATUR for airport gate assignment.
3) Experimenting the performance of Random Forest and GCN for arrival delay prediction.
4) Analyzing the effect of predicted delays on flight conflicts and gate assignments.